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International Journal of Systems Science Volume 35, 2004 - Issue 1
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Original Articles

A multiple-population evolutionary approach to gate matrix layout

A. Mendes School of Electrical Engineering and Computer Science, University of Newcastle, Callaghan, NSW, 2308, Australia E-mail: [email protected]
&
A. Linhares EBAPE/FGV, Praia de Botafogo, 190, 22.250-900 Rio de Janeiro—RJ—Brazil
Pages 13-23 | Received 29 Apr 2002, Accepted 03 Dec 2003, Published online: 23 Feb 2007

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L. De Giovanni, G. Massi & F. Pezzella. (2013) An adaptive genetic algorithm for large-size open stack problems. International Journal of Production Research 51:3, pages 682-697.
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Articles from other publishers (8)

Vinicius Gandra Martins Santos & Marco Antonio Moreira de Carvalho. (2018) Adaptive large neighborhood search applied to the design of electronic circuits. Applied Soft Computing 73, pages 14-23.
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Júnior Rhis Lima & Marco Antonio M. Carvalho. (2017) Descent search approaches applied to the minimization of open stacks. Computers & Industrial Engineering 112, pages 175-186.
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José Fernando Gonçalves, Mauricio G. C. Resende & Miguel Dias Costa. (2016) A biased random-key genetic algorithm for the minimization of open stacks problem. International Transactions in Operational Research 23:1-2, pages 25-46.
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James J. Cochran, Louis A. CoxJr.Jr., Pinar Keskinocak, Jeffrey P. Kharoufeh & J. Cole SmithPablo Moscato, Regina Berretta & Carlos Cotta. 2011. Wiley Encyclopedia of Operations Research and Management Science. Wiley Encyclopedia of Operations Research and Management Science.
Alexandre Linhares & Horacio Hideki Yanasse. (2008) Search intensity versus search diversity: a false trade off?. Applied Intelligence 32:3, pages 279-291.
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Pablo Moscato & Carlos Cotta. 2010. Handbook of Metaheuristics. Handbook of Metaheuristics 141 183 .
Chun Che Fung, Jia-Bin Li & Douglas G. Myers. 2006. Advances in Machine Learning and Cybernetics. Advances in Machine Learning and Cybernetics 889 897 .
Alexandre C. M. Oliveira & Luiz A. N. Lorena. 2005. Evolutionary Computation in Combinatorial Optimization. Evolutionary Computation in Combinatorial Optimization 166 176 .

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